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DBMS > Amazon Aurora vs. Databricks vs. SWC-DB vs. Yanza

System Properties Comparison Amazon Aurora vs. Databricks vs. SWC-DB vs. Yanza

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabricks  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A high performance, scalable Wide Column DBMSTime Series DBMS for IoT Applications
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column storeTime Series DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteaws.amazon.com/­rds/­aurorawww.databricks.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
yanza.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databricks.com
DeveloperAmazonDatabricksAlex KashirinYanza
Initial release2015201320202015
Current release0.5, April 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL V3commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesyesnono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedhostedLinuxWindows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesyesnono
Secondary indexesyesyesno
SQL infoSupport of SQLyeswith Databricks SQLSQL-like query languageno
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Thrift
HTTP API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Python
R
Scala
C++any language that supports HTTP calls
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnono
Triggersyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardno
More information provided by the system vendor
Amazon AuroraDatabricksSWC-DB infoSuper Wide Column DatabaseYanza
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon AuroraDatabricksSWC-DB infoSuper Wide Column DatabaseYanza
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